How can model driven development improve software architecture quality?

It's vital to underscore the importance of context in software development. Not every project requires an auto-scaling, 12-factor application. The key is to tailor the architecture to the specific needs and constraints of the project. For instance, in smaller-scale projects or those with unique compliance requirements, simplicity, and specific customizations might take precedence over scalability and modularity. The context – be it the size of the project, the industry, the regulatory environment, or available resources – often dictates the most suitable architectural approach.

I think you also need to consider sustainability - businesses change over time and a sustainable architecture should be able to flex and adapt to reflect the needs of the business over time.

These quality attributes, such as reliability and security, are architecture characteristics. It is important to select up to 7 of these characteristics as the priorities for the architecture and the product. Why up to 7? Because you will find it very hard to architect for any more than that. Some of these characteristics can be considered implicit, and taken into consideration alongside your 7, including security and feasibility. The quality of your architecture is then measured against how well it meets your 7, and the implicit characteristics. It is not measured against other characteristics, as it is just not possible to architect to all possible architecture characteristics at the same time.

One of the main challenges I see is how companies is how they flex back and forth between understanding the value of architecture to meet stakeholder expectations. The flexing goes back and forth between valuing architecture and then almost ditching it in tougher times. Architecture is important from the start and should always be in processes. Without a good architectural design with weighing tradeoffs, constraints, business goals, etc, teams get into jams where they need to roll back or completely rewrite frameworks and solutions. Quality also suffers as a result.

La calidad de la arquitectura de software es un aspecto crítico del desarrollo de software. Una arquitectura de software de alta calidad puede mejorar la eficiencia, la efectividad y la satisfacción del usuario del sistema, mientras que una arquitectura de baja calidad puede llevar a problemas de rendimiento, confiabilidad y mantenibilidad. Para lograr una arquitectura de software de alta calidad, es importante seguir buenas prácticas de dise?o, como la separación de preocupaciones, la abstracción y el acoplamiento

There is a famous saying that all models are wrong, but some are useful. Bear this in mind as it is true. Your model is an abstraction of reality and therefore cannot be exact. One way to help your model be useful is to involve all experts, be they business, customers or technical. Make the process of creating the model collaborative, using a process such as Event Storming or Domain Storytelling. Your model will start in the problem domain, where you will start to create a ubiquitous language (like a glossary for your product and domain). Once you have the problem modelled you will move into the solution domain, which will likely add to your ubiquitous language. DDD (domain driven design) is an excellent method to supplement modelling.

A risk here is that models can become too tightly coupled to the problem domain, particularly if they use language and conventions specific to a particular industry. Taking a more abstract approach when modelling and using generic terminology and nomenclature can help engineers recognise existing solutions and solved problems from other industries that they can recycle to accelerate their work.

You need to ensure that you have a coherent dictionary that all parties agree to otherwise you can be exposed to misconceptions particularly when it comes to artifacts.

Smaller models are more easily shared than large complex ones - classical inheritance can help you decompose models and a composable design system can let you mix and match properties between models - I like to treat my atomic models like Lego pieces and clip them together to deliver emergent complexity - it takes more up-front analysis but leads to highly modular systems.

One practical way to approach a large scale architecture is to first identify a few high-level software components that together will satisfy the requirements of your system. And then you can decompose each of those high-level components further into sub-components, each with a more refined set of requirements to fulfill. Then continue this recursive decomposing process until you are left with clearly defined atomic software components. You can team up with other architects to decompose separate components in parallel and divide the responsibility for developing the resulting sub-architectures.

Consider that you do not need to use a DSL (domain specific language) or something else that can be converted directly to code in order to create a model. There are many collaborative techniques, such as Scenario Casting, Event Storming and Domain Storytelling which help you to create a model which can then be refined before writing any code.